Nothing
#' @keywords internal
# Could maybe made external
# Calculates the forward probabilities, used for sampling the state sequence
# Based on Zuchini 2016.
# for categorical observations only.
cat_Mult_HMM_fw <- function(x, m, emiss, n_dep, gamma, delta = NULL){
if(is.null(delta)) {
delta <- solve(t(diag(m) - gamma + 1), rep(1, m))
}
n <- dim(x)[1]
lalpha <- alpha_prob <- matrix(NA, m, n)
inp <- rep(list(NULL), n_dep)
for(q in 1:n_dep){
inp[[q]] <- t(emiss[[q]][,x[,q]])
}
allprobs <- Reduce("*", inp)
foo <- delta * allprobs[1, ]
sumfoo <- sum(foo)
alpha_prob[, 1] <- foo/sumfoo
lscale <- log(sumfoo)
lalpha[, 1] <- log(alpha_prob[, 1]) + lscale
for (i in 2:n){
foo <- alpha_prob[, (i - 1)] %*% gamma * allprobs[i, ]
sumfoo <- sum(foo)
alpha_prob[, i] <- foo / sumfoo
lscale <- lscale + log(sumfoo)
lalpha[, i] <- log(alpha_prob[, i]) + lscale
}
list(la = lalpha, forward_p = alpha_prob)
}
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